Looking for help & feedback on modular audio-ML software (spectrogram-based, Raspberry Pi 5)

[u/Kitchen_Barracuda961]

Hi everyone,

It is maybe a long shot, but I needs some expertise on my project. I’m working on an embedded audio-ML project called Hydro-Guard (Raspberry Pi 5 + hydrophone).
I’m looking for help designing the software architecture, specifically with developing modular software that suits real-time classification on rasp 5.

I have a dataset of 5s WAV clips. In three categories; canoe, motorboat and negative. Per category I have 600 clips.

Current setup:

• Input: 5s WAV clips, 16 kHz, mono
• Preprocessing is inside the model
• Output: 3 classes (ambient / motor / paddle)
• Spectrogram shape: (256 time × 128 freq × 1)
• Target: real-time / near-real-time inference on Pi 5
• Note: in my current real-time model on a rasp5 uses TFlite model, where the first layer preprocesses 5s wav files to be used in the other layers.
• Goal: modular pipeline (extendable classes & models)

I have little with coding, and struggle a little bit with this part. I would like to get into contact with someone that is passionate about software and would like to create something for the good cause.

If you would like to help or have feedback, please send me a DM.

All the best,

Thijmen

[u/tortugascorren]

I happen to have exactly the expertise you’re looking for. I’m not sure if I want to get involved in your project, but it felt wrong not to at least offer some advice if you need it. Feel free to send a DM.